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Immune cell sequencing after allogeneic hematopoietic cell transplantation [scRNA-seq]

GSE290864 Homo sapiens (human) Single-cell RNA-seq 34 samples Submitted 2026/03/01 Platform GPL34284Platform GPL24676
At a glance

Single-cell RNA-seq · human · 34 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Homo sapiens (human)
Samples
34 samples: 34 samples, each with a distinct title — no replicated groupsGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper
Regulatory-like FOXP3+Helios+CD4+ T conventional cells correlate with T-cell activation after Orca-T immunotherapyBlood · 2026
Summary (written by the submitters)
Allogeneic hematopoietic stem cell transplantation (allo-HSCT) is a curative therapy for hematologic malignancies. The primary non-relapse complication after allo-HSCT is graft-versus-host disease (GVHD). The use of T regulatory (Treg) cells to prevent GVHD has emerged as a promising allogeneic T cell immunotherapy in the form of Orca-T.
Read the full summary ↓
However, the precise differences in immune states which may influence clinical outcomes after Orca-T compared with unmanipulated peripheral blood stem cell (PBSC) grafts remain unexplored. Using peripheral blood specimens longitudinally collected between 3 weeks and one year after leukemia treatment, we examined single-cell mRNA sequencing (scRNA-seq) analysis of 16 HLA-matched patients receiving either Orca-T or unmanipulated PBSC grafts.
Published in
Regulatory-like FOXP3+Helios+CD4+ T conventional cells correlate with T-cell activation after Orca-T immunotherapy
Bader CS, Killian S, Iliopoulou BP et al. · Blood 2026 · PMID 41758930 · doi:10.1182/blood.2025031545
This dataset
Open GSE290864 in finder → Find more human RNA-seq datasets →
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE290864_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1229550 and SRA study SRP566834. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41758930) ↗
Study design
34 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 34 sample titles: 34 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study
Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.